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Below is a selection of tools and technologies I use in daily work on perception, learning-based control, and robotic systems.
Frameworks and libraries
Optimization and deployment
Data processing and experimentation
Experiment tracking
Core libraries
Methods and models
- Object detection (YOLO, Faster R-CNN, SSD)
- Semantic and instance segmentation (Mask R-CNN and related architectures)
- Pose estimation (OpenPose, MediaPipe)
- RGB-D perception and depth-based scene understanding
- Data augmentation and preprocessing pipelines
Used mainly for model serving, experiment dashboards, internal tools, and lightweight system interfaces.
Technologies used in mobile robotics projects, simulation environments, and deployment on embedded platforms.
Additional experience includes:
- Embedded systems and microcontroller-based platforms
- Real-time data acquisition and processing
- Simulation-to-real transfer in robotic learning pipelines
- System monitoring, diagnostics, and telemetry
- π Website: https://piotrgapski.info.pl
- π§ Email: [email protected]
- πΌ LinkedIn: https://www.linkedin.com/in/piotr-gapski
Β© 2026 Piotr Gapski
Machine Learning Β· Computer Vision Β· Robotics Engineer